Businesses do not have the luxury to go on an exploratory mission with business intelligence and analytics. Save the moonshots and boldly going where none have gone before for NASA.
With the widespread use of business data and ramifications of COVID-19, your business needs meaningful and actionable insights fast. How do data-driven organizations routinely get the most from the data? In our experience, it’s by building a robust business intelligence strategy to guide all of the BI activities.
Here is a snapshot of the added value the right data analytics roadmap provides for those businesses that have relied on a provisional approach to their data.
The average organization manages and stores terabytes of structured and unstructured data, with more gigabytes generated every day. And all of that data is not created equal. Without a data strategy, business users can struggle to find and leverage strategic data sets from the growing mountain of information. Can valuable and strategic insights be obtained this way? Yes, but this rudderless approach to analysis offers hit or miss results.
A BI strategy helps businesses answer some essential questions up front that improve their ability to maximize insights.
By answering those questions, businesses are much better equipped to conduct analytics that satisfies urgent needs. Take healthcare providers. Most organizations are eager to improve care outcomes and reduce readmission rates but may not know how to identify which of their patient discharges will result in swift readmission.
By acknowledging the challenge (a lack of insight into the factors of readmission) and the necessary data sources (EHRs, hospital management software, and others) to consolidate, healthcare providers can conduct predictive analysis that risk scores patience for readmission. Taking time during the business intelligence strategy process to outline challenges, essential data, and techniques can help healthcare (or any) organization to accelerate their access to strategic insight.
A firm business intelligence strategy enables organizations to hit their goals with greater consistency. One reason is that evaluating and defining the right KPIs is a cornerstone of an effective data analytics roadmap. When the preliminary stage of BI and analytics accounts for your key metrics, you can obtain or design tools or processes that maximize those goals.
Here’s a scenario. Suppose a manufacturing company is building a BI dashboard for their team. In that case, the right business intelligence strategy will allow them to determine which reports will offer the most incredible value—providing easy access to productivity by machine or units lost per machine to learn about critical metrics like production downtime or return on assets. No matter the industry, your ability to incorporate KPIs into your analytics platforms and processes can elevate your overall ROI.
Data architecture often evolves haphazardly, creating obstacles to practical analysis ranging from data silos and data inconsistency to inaccessibility and fragmented ownership. For any self-service reporting or analysis level, your team needs access to data tools and platforms that are dependent upon exceptional data management practices. Again, a comprehensive business intelligence strategy can help.
The complex array of disparate data sources can be challenging to wrangle without the right strategy.
The right BI strategy is essential to resolving these questions fast and efficiently. Once in place, both strategy and data management can improve through a cycle of mutual reinforcement.
What about the results? Let’s look at this from a retail business perspective. When data from CRMs, e-commerce platforms, social media, and other sources are combined, there’s incredible potential for insight. Creating consistency and accuracy across all of these different data sources can be complicated, yet retailers that have identified the most relevant data sets by creating a data strategy roadmap have fought half the battle.
Retailers can then create a data pipeline that transforms and loads the separate source systems into a consolidated business layer that is quick and easy for authorized users to leverage. They can then identify buyer patterns, revenue opportunities, and customer motivations that might have otherwise been out of reach.
This is just the tip of the iceberg for the potential value of a business intelligence strategy. At the end of the process, the roadmap can provide compounded benefits to your organization that impact every function and goal. However, those businesses that are new to the concept of a business intelligence strategy need assistance accelerating the ramp-up to effective reporting and analytics. Whether that involves hiring data analysts or leveraging a team, the end results are worth the time and effort.